49 datasets found
  1. h

    genz-slang-dataset

    • huggingface.co
    Updated Oct 2, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GMLB trio 2024 (2024). genz-slang-dataset [Dataset]. https://huggingface.co/datasets/MLBtrio/genz-slang-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 2, 2024
    Dataset authored and provided by
    GMLB trio 2024
    Description

    Dataset Details

    This dataset contains a rich collection of popular slang terms and acronyms used primarily by Generation Z. It includes detailed descriptions of each term, its context of use, and practical examples that demonstrate how the slang is used in real-life conversations. The dataset is designed to capture the unique and evolving language patterns of GenZ, reflecting their communication style in digital spaces such as social media, text messaging, and online forums. Each… See the full description on the dataset page: https://huggingface.co/datasets/MLBtrio/genz-slang-dataset.

  2. Gen Z's Awareness, Societal Action, and Understanding of Waste Management...

    • zenodo.org
    Updated Jun 18, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Yudhistira Sundjaya; Yudhistira Sundjaya (2025). Gen Z's Awareness, Societal Action, and Understanding of Waste Management Dataset (2025) [Dataset]. http://doi.org/10.5281/zenodo.15646587
    Explore at:
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Yudhistira Sundjaya; Yudhistira Sundjaya
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains the results of a survey conducted via Google Forms to assess Generation Z’s understanding, environmental awareness, and social action related to waste management during the Eid al-Fitr holiday season. The survey included an infographic guide as a stimulus to evaluate how visual media supports behavioral change and sustainability education among youth. The dataset also contains the result that had been transcribed from an interview with carbon expert.

    The dataset, exported from Google Forms in XLSX format, includes respondents’ demographic information, their interpretation of the infographic content, their level of environmental awareness, and their reported or intended waste management practices during the holiday. The dataset from interviews with carbon expert, exported in DOCX format.

    This dataset is valuable for researchers in environmental education, youth studies, sustainability communication, and behavioral change research.

    Format: XLSX (exported from Google Forms)
    Number of Respondents: 6
    Language: Indonesia
    License: Creative Commons Attribution 4.0 International (CC BY 4.0)
    Data Collection Method: Online survey using Google Forms
    Data Collection Period: 4 April 2025

  3. Gen Z Money Spending Dataset

    • kaggle.com
    Updated Jan 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Anand Kumar (2025). Gen Z Money Spending Dataset [Dataset]. https://www.kaggle.com/datasets/manandkumar/gen-z-money-spending-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 31, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Anand Kumar
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset provides insights into the spending habits of Gen Z (ages 18-27) across various categories such as rent, groceries, entertainment, education, savings, and more. It contains 1700 records and 15 financial attributes, making it a valuable resource for financial trend analysis, budgeting studies, and machine learning applications in personal finance.

  4. e

    Generation Z and and Corona (July 2021) - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Jul 15, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2021). Generation Z and and Corona (July 2021) - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/29cd01f3-5205-506d-95c9-e43aaf51d1ae
    Explore at:
    Dataset updated
    Jul 15, 2021
    Description

    On behalf of the Press and Information Office of the Federal Government, the opinion research institute Kantar conducted a target group survey of the ´Generation Z´. For this purpose, 1,022 people between the ages of 14 and 24 were surveyed online between 05 and 18 July 2021. The focus of the survey was on the values and orientation of the generation, their situation in the pandemic, political interest and information behaviour as well as political and social attitudes. In order to map the influence of the corona pandemic on the attitudes and social image of Generation Z, the results of this survey were compared with a survey from 2019. Current life circumstances: life satisfaction; highest school-leaving qualification of father and mother; material situation: frequency of renunciation for financial reasons; source of money (from own work, from parents, from state support, from elsewhere); primary source of money; negative effects of the Corona crisis on personal income; organisation of distance learning (communication via a digital learning platform, via video conference, via e-mail, via messenger/chats such as e.g. WhatsApp, via a cloud, by telephone, by post or by other means); agreement with statements on the situation in schools/colleges (I was able to concentrate well on my tasks at home, I missed direct contact with my classmates/ fellow students, my grades deteriorated during the pandemic, distance learning at my school/college worked well, I had insufficient equipment to follow lessons, the accessibility of teachers was very good even in times of distance learning, learning became more strenuous for me during the pandemic); opinion on the future recognition of school, university or professional degrees made during the Corona pandemic; leisure activities during the pandemic (less sport since the beginning of the pandemic than before, relationships with friends have deteriorated during the pandemic, significantly more time on the internet since the beginning of the pandemic than before, started a new hobby during the pandemic); vaccination status; likelihood of Corona vaccination. 2. Values and attitudes: personally most important life goals (e.g. self-discovery, independence, enjoying life, career, etc.); importance of various aspects for pursuing a profession (secure job, adequate income, interesting work that is fun, compatibility of private life and profession (work-life balance), career opportunities, responsibility, opportunities for further training and development); comparison of values : comparison of values Corona: extensive collection of data for infection protection vs. data protection, especially young vs. especially old people have suffered from the pandemic, pandemic as a chance for change vs. after the pandemic back to the usual normality, comparison of values State: debts in favour of education and infrastructure not a problem vs. always a burden for future generations, active role of the state for important future tasks such as climate protection and educational justice vs. leaving a passive role and shaping of the future to society and the economy, orienting politics towards future generations vs. protecting the interests of those who have already made a contribution to society, comparison of lifestyle values: conscious renunciation in favour of sustainability vs. doing what I feel like doing, doing without in favour of health vs. having fun in the foreground, self-realisation vs. putting aside one´s own needs in favour of one´s personal environment, today´s generation has completely different values than the generation before it vs. in principle very similar values as the generation before it). 3. Media and information: interest in politics; points of contact with politics in everyday life (e.g. media consumption, when using social networks, in personal conversations with friends and family, at work, at school or university, in public spaces, in leisure time/hobbies); being informed about politics; most frequently used sources of political information (media) (e.g. news programmes on TV, talk shows on TV, websites of public institutions and authorities, etc.). e.g. news programmes on TV, talk shows on TV, websites of public institutions and authorities, satire programmes on TV, etc.); change in political information behaviour in the Corona pandemic. 4. Politics and society: satisfaction with democracy; opinion on democracy as an idea; need for reform of politics in Germany; most important political problems in Germany (open); satisfaction with the work of the federal government; trust in institutions (judiciary, environmental and aid organisations such as Greenpeace or Amnesty International, public health authorities such as the Robert Koch Institute, federal government, Bundestag, police, churches, school/university); perception of social lines of conflict (between rich and poor, employers and employees, young and old, foreigners and Germans, East Germans and West Germans, women and men, people in the city and people in the countryside); attitudes towards Corona (politicians take young people´s concerns seriously, young people received sufficient financial support from the state during the pandemic, young people´s needs were not taken into account enough by politicians during the Corona pandemic, the Corona pandemic will affect my generation´s future opportunities in the long term, my generation will benefit significantly from the awakening after the Corona pandemic, the Corona crisis has changed my perspective on many things in life, young people´s career opportunities have deteriorated as a result of the pandemic); agreement with various statements on Corona vaccination (children and young people aged 12 and over should also be vaccinated against Corona, young people currently have to wait too long for a vaccination appointment, vaccination prioritisation should have been lifted earlier, vaccination of young people against Corona is not necessary, there should be compulsory vaccination for schoolchildren, I personally feel that Corona vaccinations in Germany are treated fairly); currently appropriate measures to support children and young people (open). 5. Future perspectives: assessment of personal future opportunities; assessment of the future opportunities of one´s own generation in Germany; future vision of politics: agreement with various statements (a council of randomly selected citizens should be created to draw up political recommendations for the federal government, voting in elections should be possible via app, the voting age in federal elections should be lowered to 16, the population should be represented in the Bundestag by means of quotas, the population should vote directly on important political issues by referendum). Demography: age; sex; federal state; current attendance at school, college or university; type of educational institution currently attended; highest level of education attained to date; employment; subjective class classification; housing situation; household size; party sympathies; migration background. Additionally coded was: serial number; city size; weighting factor. Im Auftrag des Presse- und Informationsamt der Bundesregierung hat das Meinungsforschungsinstitut Kantar eine Zielgruppenbefragung der „Generation Z“ durchgeführt. Dazu wurden im Zeitraum vom 05. – 18. Juli 2021 1.022 Personen zwischen 14 und 24 Jahren online befragt. Die Schwerpunkte der Befragung lagen auf den Werten und Orientierung der Generation, ihrer Situation in der Pandemie, dem politischen Interesse und Informationsverhalten sowie auf den politischen und gesellschaftlichen Einstellungen. Um den Einfluss der Coronapandemie auf die Einstellungen und das Gesellschaftsbild der Generation Z abzubilden, wurden die Ergebnisse dieser Befragung mit einer Befragung aus dem Jahr 2019 verglichen. Aktuelle Lebensumstände: Lebenszufriedenheit; höchster Schulabschluss von Vater und Mutter; materielle Situation: Häufigkeit des Verzichts aus finanziellen Gründen; Geldquelle (aus eigener Arbeit, von den Eltern, aus staatlicher Unterstützung, von woanders her); primäre Geldquelle; negative Auswirkungen der Corona-Krise auf das persönliche Einkommen; Organisation des Fernunterrichts (Kommunikation über eine digitale Lernplattform, per Videokonferenz, per E-Mail, per Messenger/Chats wie z.B. WhatsApp, über eine Cloud, per Telefon, per Post oder auf sonstige Weise); Zustimmung zu Aussagen zur Situation in Schulen/ an Hochschulen (ich konnte mich zu Hause gut auf meine Aufgaben konzentrieren, der direkte Kontakt zu meinen Mitschüler/innen/ Kommilitonen/innen hat mir gefehlt, meine Noten sind während der Pandemie schlechter geworden, der Fernunterricht an meiner Schule/ Hochschule hat gut funktioniert, ich hatte nur ungenügende Ausstattung zur Verfügung, um dem Unterricht folgen zu können, die Erreichbarkeit der Lehrkräfte war auch in Zeiten des Fernunterrichts sehr gut, das Lernen ist für mich während der Pandemie anstrengender geworden); Meinung zur künftigen Anerkennung von Schul-, Universitäts- oder Berufsabschlüssen, die während der Corona-Pandemie gemacht wurden; Freizeitgestaltung während der Pandemie (seit Beginn der Pandemie weniger Sport als davor, Beziehungen zu Freunden haben sich in der Pandemie verschlechtert, seit Beginn der Pandemie deutlich mehr Zeit im Internet als davor, in der Pandemie ein neues Hobby begonnen); Impfstatus; Wahrscheinlichkeit einer Corona-Impfung. 2. Werte und Einstellungen: persönlich wichtigste Lebensziele (z.B. Selbstfindung, Unabhängigkeit, Leben genießen, Karriere, etc.); Wichtigkeit verschiedener Aspekte für die Ausübung eines Berufs (sicherer Arbeitsplatz, angemessenes Einkommen, interessante Arbeit, die Spaß macht, Vereinbarkeit von Privatleben und Beruf (Work-Life-Balance), Karrieremöglichkeiten, Verantwortung, Weiterbildungs- und Entwicklungsmöglichkeiten); Gegenüberstellung von Werten :

  5. Data from: Gen Z and Beyond: A Survey for Every Generation, 2021-2023

    • beta.ukdataservice.ac.uk
    Updated 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    datacite (2023). Gen Z and Beyond: A Survey for Every Generation, 2021-2023 [Dataset]. http://doi.org/10.5255/ukda-sn-856374
    Explore at:
    Dataset updated
    2023
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    DataCitehttps://www.datacite.org/
    Description

    The Zoroastrian community today faces many challenges, some of which are deep-rooted and complex with no easy fix or resolution. It was proposed by members of the community that an independent research project should be conducted to help understand the community as it exists today. Gen Z and Beyond: A Survey for Every Generation was a completely anonymous survey for Iranian / Parsi / Irani Zoroastrians. It was conducted by researchers at the SOAS Shapoorji Pallonji Institute of Zoroastrian Studies (SSPIZS). SOAS was chosen as a neutral platform for research, so that the researchers would not support any particular outcome from the survey. The project was approved by the SOAS Research Ethics Panel. There has been no other survey of this nature undertaken on the global Zoroastrian community. The survey questionnaire was wide-ranging and included questions about domestic and family life, professional aspirations, religious observances and beliefs, philanthropy, entrepreneurship, immigration, community engagement and other issues of importance and relevance to the (Iranian / Parsi / Irani) Zoroastrian community. The purpose of conducting the survey was to produce a report and dataset that could be of use to community leaders and researchers in the present and future.

  6. Generation Z and Decision Making

    • kaggle.com
    Updated Feb 12, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Vrindha Moka (2022). Generation Z and Decision Making [Dataset]. https://www.kaggle.com/vrindhamoka/generation-z-and-decision-making/metadata
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 12, 2022
    Dataset provided by
    Kaggle
    Authors
    Vrindha Moka
    Description

    How it Started

    I was interested in collecting data about how Generation Z makes decisions because college is on the horizon for my classmates and me. We are becoming the leaders, entrepreneurs, and creators of tomorrow and behind every successful person, is their ability to make the right decision at the right time.

    How I Collected my Data

    I collected my data through google forms and before the answers started to trickle in, I created my own hypothesis. I thought that most students in Generation Z would not be afraid to make decisions and that since they are one of the smartest generations, they would be able to tackle the task of picking which college is best for them and why.

    Inspiration

    I am very much aware that a lot of research is being done to find out more about Generation Z, but I was so inspired by my research coach, Coach Jo, who is currently doing research with Dr. Peggy Dawson about Generation Z and Productivity. I learned that Generation Z is by far the smartest generation, but our attention spans are cut short because of how much we use technology and the internet. This research will help find out whether technology and making decision affects Generation Z and how we, as a society, can make better decisions for better futures.

  7. h

    gen-z-translation

    • huggingface.co
    Updated May 6, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    AI Maker Space (2024). gen-z-translation [Dataset]. https://huggingface.co/datasets/ai-maker-space/gen-z-translation
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 6, 2024
    Dataset authored and provided by
    AI Maker Space
    Description

    ai-maker-space/gen-z-translation dataset hosted on Hugging Face and contributed by the HF Datasets community

  8. Z

    Song Preference CLassification Dataset for Gen Z

    • data.niaid.nih.gov
    • zenodo.org
    Updated Oct 8, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Chandresh Pravin (2020). Song Preference CLassification Dataset for Gen Z [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4071943
    Explore at:
    Dataset updated
    Oct 8, 2020
    Dataset provided by
    Chandresh Pravin
    Varun Ojha
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains audio recordings of 12 different accents across the UK: Northern Ireland, Scotland, Wales, North East England, North West England, Yorkshire and Humber, East Midlands, West Midlands, East of England, Greater London, South East England, South West England. We split the data into a Male: Female ratio of 1:1. The audio dataset was compiled using opensource YouTube videos and it a collation of different accents, the audio files were trimmed for uniformity. The Audio files are of length 30 seconds, with the first 5 seconds and last 5 seconds of the signal being blank. We also resample the audio signals at 8 kHz, again for uniformity and to remove any noise present in the audio signals whilst retaining the underlying characteristics. The intended application of this dataset was to be used in conjunction with a deep neural network for accent and gender classification tasks.

    This dataset was recorded for an experimentation looking into applying machine learning techniques for the task of classifying song preference amongst generation Z (18 to 24 years) participants. We define a labelling system corresponding to specific songs with 5 ratings: hate, dislike, neutral, like and love. The songs used for this experiment were chosen due their success for various awards, such as the BRIT awards (BRIT), Mercury Prize (MERC), Rolling Stone most influential albums (ROLS). They are as shown:

    S1: One Kiss by Calvin Harris and Dua Lipa (BRIT)
    
    
    S2: Don't Delete the Kisses by Wolf Alice MERC)
    
    
    S3: Money by Pink Floyd (ROLS)
    
    
    S4: Shotgun by George Ezra (BRIT)
    
    
    S5: Location by Dave (MERC)
    
    
    S6: Smells Like Teen Spirit by Nirvana (ROLS)
    
    
    S7: God's Plan by Drake (BRIT)
    
    
    S8: Breezeblocks by alt-J (MERC)
    
    
    S9: Lucy In The Sky With Diamonds by The Beatles (ROLS)
    
    
    S10: Thank U, Next by Ariana Grande (BRIT)
    
    
    S11: Shutdown by Skepta (MERC)
    
    
    S12: Billie Jean by Micheal Jackson (ROLS)
    

    A Unicorn Hybrid Black was used for recording the EEG data from the participants whilst they were played the control songs listed above. For each of the 12 total song played to a participant during the experiment, there were 8 EEG lead recordings measured of length 20 seconds, with the first 5 seconds and the last 5 seconds being blank for control purposes. The EEG signals were sampled at 250 Hz by the Unicorn Hybrid Black devices, which also filtered the signals to be between 2Hz to 30 Hz in order to remove any noise recorded during the experimentation. There are approximately 5000 data points per reading of a given song, with there being 12 songs played to a total of 10 participants.

  9. m

    Dataset on the Influence Of Digital Literacy On Intention to Use Investment...

    • data.mendeley.com
    Updated Mar 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jhony Tan (2025). Dataset on the Influence Of Digital Literacy On Intention to Use Investment Applications in Generation Z: A Case Study on Financial Products [Dataset]. http://doi.org/10.17632/273p5pc7hd.1
    Explore at:
    Dataset updated
    Mar 18, 2025
    Authors
    Jhony Tan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains responses from a survey analyzing the impact of digital literacy on Generation Z’s intention to invest in financial products through investment applications. The data includes key variables such as digital literacy levels, investment awareness, behavioral intention, perceived ease of use, perceived risk, and demographic factors. The study aims to identify the extent to which digital literacy influences financial decision-making among young investors and how technology adoption plays a role in shaping their investment behavior.

    The dataset is structured to support statistical analysis, hypothesis testing, and predictive modeling, making it valuable for academic research, business insights, and financial technology development.

  10. h

    genz-slang-pairs-1k

    • huggingface.co
    Updated Jun 9, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Programmer-RD-AI (2025). genz-slang-pairs-1k [Dataset]. http://doi.org/10.57967/hf/5742
    Explore at:
    Dataset updated
    Jun 9, 2025
    Authors
    Programmer-RD-AI
    License

    https://choosealicense.com/licenses/cc/https://choosealicense.com/licenses/cc/

    Description

    Gen Z Slang Pairs Corpus (1 K)

    The Gen Z Slang Pairs Corpus (1 K) contains 1,000 everyday English sentences alongside their Gen Z–style slang rewrites. This dataset is designed for style-transfer, informal-language generation, and paraphrasing research. Use it to train models that transform formal or neutral sentences into expressive, youth‑oriented slang.

      Dataset Details
    

    This dataset was generated programmatically using OpenAI GPT-4.1 Nano.

    Language: English… See the full description on the dataset page: https://huggingface.co/datasets/Programmer-RD-AI/genz-slang-pairs-1k.

  11. g

    Life in Generation Z | gimi9.com

    • gimi9.com
    Updated Oct 27, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2020). Life in Generation Z | gimi9.com [Dataset]. https://gimi9.com/dataset/uk_life-in-generation-z/
    Explore at:
    Dataset updated
    Oct 27, 2020
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This is a survey of over 3,000 young Londoners that was completed in June 2020 in partnership with the Museum of London. This focuses on the key issues and concerns affecting young people aged between 16-24 and reviews the challenges they face and what needs to happen to help young people thrive across the capital. This dataset is being reviewed. The data will be made available again soon.

  12. AI-Driven Journeys: The Adoption of Artificial Intelligence (AI) Chatbots in...

    • figshare.com
    csv
    Updated Jan 10, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    JerĂłnimo Paiva (2025). AI-Driven Journeys: The Adoption of Artificial Intelligence (AI) Chatbots in Tourism and Hospitality by Gen Z (Dataset) [Dataset]. http://doi.org/10.6084/m9.figshare.28184666.v1
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 10, 2025
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    JerĂłnimo Paiva
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The dataset consists of responses collected via an online questionnaire targeting Generation Z individuals in Portugal. It focuses on understanding the adoption of AI-driven chatbots in the tourism and hospitality industries. The data includes demographic information, behavioral variables, and responses to constructs from the AI Device Use Acceptance (AIDUA) model, such as emotional reaction, performance expectancy, anthropomorphism, and social influence.

  13. d

    Student Marketing Data | USA Coverage | Millennial and Gen Z Contact Data

    • datarade.ai
    .csv
    Updated Apr 27, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    BIGDBM (2023). Student Marketing Data | USA Coverage | Millennial and Gen Z Contact Data [Dataset]. https://datarade.ai/data-products/bigdbm-3rd-party-us-consumer-millennial-and-gen-z-package-bigdbm
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Apr 27, 2023
    Dataset authored and provided by
    BIGDBM
    Area covered
    United States
    Description

    Demographic and PII data (including emails, phone numbers, and addresses) for the US Millennial and Gen Z population segments. Fully opt-in and CCPA compliant (direct submission from the individuals). 30 million+ population.

    High success and conversion rates for direct marketing, targeted ads, identity verification, and demographic research.

    This data can be merged into the BIGDBM Consumer dataset or have specific data fields appended from the BIGDBM Consumer dataset.

    BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

  14. d

    Brand Activism and GenZ

    • dataone.org
    Updated Dec 16, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Scalvini, Marco (2023). Brand Activism and GenZ [Dataset]. http://doi.org/10.7910/DVN/6HNVQ8
    Explore at:
    Dataset updated
    Dec 16, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Scalvini, Marco
    Description

    The interview protocol aims to gauge their perceptions and responses toward brand activism, with a focus on their interactions with brands endorsing social issues. Within this dataset, interviewees unpack their perspective on Gen Z attributes and evaluate their resonance with prevalent depictions. Central to the interview is the participants' feedback on prominent brand campaigns such as Nike's "JUST DO IT," Gillette's "We Believe," and Libresse/Bodyform's "Viva la Vulva," to name a few. Their analyses unveil perceptions of brand genuineness, the synergy between a brand's image and its advocated social concerns, and the overarching ramifications of brand activism on consumer purchasing decisions. In addition, the dataset broaches essential themes like social credibility, the influence of brand spokespeople, geographical variances in brand activism, and the prospective outcomes for customer fidelity and product pricing. This collection offers an in-depth glimpse into the intricate dynamics between Gen Z and brands during this period of intensified social and political awareness. This dataset comprises qualitative data obtained from interviews with 37 individuals from the Gen Z demographic, predominantly aged between 20-25 years. Of these participants, 53.3% identified as male (n=20), 40% as female (n=15), and 6.7% opted not to specify their gender (n=2). The participants for these interviews were strategically sourced using the snowballing technique between 2021 and 2022. Among them, 33 are international young adults who, at some point within the last 1-2 years, were studying or employed in the Netherlands. It is noteworthy that between October 2021 and February 2022, the Netherlands observed a stringent lockdown, mandating remote work. Consequently, some interviewees, despite affiliations with Dutch organizations, were in their home countries during their respective interviews. The distribution of participants based on their continents of origin, namely North America, Europe, and Asia, and taking into account their place of residence in instances of dual citizenship, is detailed as follows: 1) Europe has the predominant representation with a sum of 20 participants; 2) North America consists of 7 participants, all originating from the USA; 3) Asia comprises 6 participants spread across four countries: Vietnam, Indonesia, Japan, and South Korea. Additionally, 4) South America is denoted by one participant from Bolivia and another participant holding dual citizenship from Argentina but currently residing in the US.

  15. U.S. mean disposable household income 2023, by generation

    • statista.com
    Updated May 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Abigail Tierney (2025). U.S. mean disposable household income 2023, by generation [Dataset]. https://www.statista.com/topics/9997/generation-z-fashion-in-the-united-states/
    Explore at:
    Dataset updated
    May 15, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Abigail Tierney
    Description

    In 2023, the disposable income of a household led by a Millennial in the United States was 97,866 U.S. dollars per year. Households led by someone born in Generation X, however, had a disposable income of around 113,886 U.S. dollars in 2023.

  16. Cultural Tourism in Vietnam from Gen Z's Perspective

    • zenodo.org
    Updated Dec 26, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Tuan Anh Le; Tuan Anh Le (2024). Cultural Tourism in Vietnam from Gen Z's Perspective [Dataset]. http://doi.org/10.5281/zenodo.14560027
    Explore at:
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Tuan Anh Le; Tuan Anh Le
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Vietnam
    Description

    This dataset is linked to the research titled Cultural Tourism in Vietnam: Theories, Policies, and Gen Z's Perspective. It contains data from 251 respondents, representing the sample used for analysis in the study. The dataset serves as the foundation for deriving key findings and insights presented in the research.

  17. f

    Data Sheet 1_Motivations behind Gen Z’s news sharing on social media: a...

    • figshare.com
    • frontiersin.figshare.com
    zip
    Updated Jun 18, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Le Dinh Hai; Xiao Yan Xiong (2025). Data Sheet 1_Motivations behind Gen Z’s news sharing on social media: a PLS-SEM study in Vietnam.zip [Dataset]. http://doi.org/10.3389/fpsyg.2025.1604723.s001
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Frontiers
    Authors
    Le Dinh Hai; Xiao Yan Xiong
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Vietnam
    Description

    This study investigates the determinants of news-sharing behavior among Generation Z users on social media in Vietnam by integrating three theoretical frameworks: Newsworthiness Theory, Uses and Gratifications Theory (U&G), and the Theory of Planned Behavior (TPB). A structural equation modeling approach (PLS-SEM) was employed to examine the relationships between perceived news value (social significance, audience relevance), user gratifications (information seeking, socializing, status seeking, entertainment, and pass-time), and psychological drivers such as Fear of Missing Out (FoMO). Data were collected from a stratified random sample of 1.224 high school and university students across six socio-economic regions. The results reveal that social significance, audience relevance, and most gratification-based motivations—excluding pass-time—significantly influence the intention to share news. FoMO was found to positively moderate the impact of information seeking and status seeking on sharing intention. Furthermore, intention to share news significantly predicted actual news-sharing behavior, with inattention to news credibility acting as a mediating factor. The findings underscore the importance of both content attributes and user psychology in shaping digital news sharing among youth. Practical implications are discussed for media organizations aiming to enhance engagement and credibility in the digital era.

  18. m

    Dataset related to the manuscript "Generation Z’s intentions towards...

    • data.mendeley.com
    Updated Oct 10, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Tamara Vlastelica (2022). Dataset related to the manuscript "Generation Z’s intentions towards sustainable clothing disposal: Extending the Theory of Planned Behavior" [Dataset]. http://doi.org/10.17632/4yxpv7ggjs.1
    Explore at:
    Dataset updated
    Oct 10, 2022
    Authors
    Tamara Vlastelica
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Research hypotheses are outlined in the manuscript. Findings of the study indicate perceived behavioral control as the most influential determinant of Generation Z clothing customers' intentions to dispose of their used clothing in a sustainable way. This implies that, in order to motivate young clothing customers to dispose of their used clothing in a sustainable way, it is of utmost importance to establish infrastructure which would faciliatate pro-environmental clothing disposal.

  19. g

    Matthew Walsham - Life in Generation Z | gimi9.com

    • gimi9.com
    Updated Oct 27, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2020). Matthew Walsham - Life in Generation Z | gimi9.com [Dataset]. https://gimi9.com/dataset/london_life-in-generation-z-
    Explore at:
    Dataset updated
    Oct 27, 2020
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Description

    This is a survey of over 3,000 young Londoners that was completed in June 2020 in partnership with the Museum of London. This focuses on the key issues and concerns affecting young people aged between 16-24 and reviews the challenges they face and what needs to happen to help young people thrive across the capital. This dataset is being reviewed. The data will be made available again soon.

  20. m

    Dataset on Gamified Digital News Platform Engagement and Continuance...

    • data.mendeley.com
    Updated Mar 6, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Angela Elviani (2025). Dataset on Gamified Digital News Platform Engagement and Continuance Intention Among Indonesian Gen Z [Dataset]. http://doi.org/10.17632/kt58rjjgmc.1
    Explore at:
    Dataset updated
    Mar 6, 2025
    Authors
    Angela Elviani
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains responses from 467 Indonesian Gen Z respondents who participated in a survey examining continuance intention in gamified digital news platforms. The dataset was collected as part of a study investigating how perceived usefulness, satisfaction, confirmation, and intrinsic motivation (competence, autonomy, relatedness) impact user engagement and retention.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
GMLB trio 2024 (2024). genz-slang-dataset [Dataset]. https://huggingface.co/datasets/MLBtrio/genz-slang-dataset

genz-slang-dataset

MLBtrio/genz-slang-dataset

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Oct 2, 2024
Dataset authored and provided by
GMLB trio 2024
Description

Dataset Details

This dataset contains a rich collection of popular slang terms and acronyms used primarily by Generation Z. It includes detailed descriptions of each term, its context of use, and practical examples that demonstrate how the slang is used in real-life conversations. The dataset is designed to capture the unique and evolving language patterns of GenZ, reflecting their communication style in digital spaces such as social media, text messaging, and online forums. Each… See the full description on the dataset page: https://huggingface.co/datasets/MLBtrio/genz-slang-dataset.

Search
Clear search
Close search
Google apps
Main menu